1, India NIFTY index and index futures
一、印度NIFTY指數及指數期貨

The full name of S&P CNX NIFTY50 NIFTY index, also called the standard & Poor's 50 stock market index, is the national stock exchange of India (NSE)'s main index, it is a market value weighted index. The index of 50 stocks selected from 22 industries, the average stock trading volume of the last six months the total stock exchange listing in the national stock exchange of India of 45124% April 10, 2007, its market capitalisation accounted for about 57192% of the total value of. So the NIFTY index is an ideal stock price index futures index.
NIFTY指數全稱S&P CNX NIFTY50，又叫標準普爾50大盤股指數，是印度國家證券交易所（NSE）的主要指數，它是一個市值加權指數。該指數的50只成份股選自于22個行業，這些股票最近六個月的平均交易額約占在印度國家證券交易所掛牌交易的股票交易總額的45124%，其2007年4月10日的市值約占總市值的57192%。所以NIFTY指數是一種比較理想的股票價格指數期貨合約的標的指數。


National stock exchange of India (NSE) in 2000 June launch of the NIFTY index futures, and permit the Singapore Stock Exchange (SGX) in 2000 September launch of the NIFTY index futures, in order to increase the volume of NSE market and NIFTY stock index futures. At present, the NIFTY stock index futures has become a stock index futures contract before the turnover of ten world. According to the British "futures options weekly", 2006 1-6 month NIFTY futures contracts trading volume for the 38850982 Zhang Heyue, ranked fourth in the world.

2, empirical research

二、實證研究

　印度國家證券交易所（NSE）于2000年6月推出NIFTY指數期貨，之后又許可新加坡證券交易所（SGX）于2000年9月推出NIFTY指數期貨，以此增加NSE市場和NIFTY股指期貨的交易量。目前，NIFTY股指期貨已經成為世界成交量前十大的股指期貨合約。根據英國《期貨期權周刊》的統計，2006年1-6月NIFTY股指期貨合約成交量為38850982張合約，排名世界第4。 

(1) the stock index daily return rate of descriptive statistics
（一）股票指數日收益率數據的描述性統計

The daily closing price of India stock index sequence selection, distribution system of India stock market rate of return. The data are from the national stock exchange of India (NSE) database http://www.nse-india.com, taking into account the national stock exchange of India launched the N IFTY stock index futures at home in June 12, 2000, from April 12, 1989 to April 12, 2010 a total of 4724 N IFTY index.
　選取印度股票指數的每日收盤價序列，系統研究印度股票市場日收益率的分布特征。本文數據全部來自于印度國家證券交易所（NSE）數據庫http：//www.nse-india.com，考慮到印度國家證券交易所于2000年6月12日在本土推出N IFTY股指期貨，選取1989年4月12日至2010年4月12日的N IFTY指數共4724#p#分頁標題#e#

Daily return series of R index has the characteristics of left deviation, kurtosis and heavy tail. The skewness and kurtosis values from =-0.08684 =9.155324, and the standard normal distribution (S=0, K=3), on the yield of skewness value is negative, showed that the distribution of the Hang Seng Index daily return is left (negative) deviation, kurtosis value is positive and significantly higher than the normal distribution of 3, showed that the India stock index the return distribution density curve tails off to the left, characteristic is extremely obvious peak and fat tail distribution. While the JB normality test also shows that the p value close to 0, indicating at least can reject the null hypothesis at the 99% confidence level, namely the stock daily return series obviously different Yu Zheng normal distribution, so we can see that the NIFTY index daily return rate relief wavy, has obvious volatility clustering. Preliminary can determine its fluctuation has ARCH effect.
(two) the establishment of data processing and model
1 stationary test
Using Eviews 6 to yield sequence R ADF unit root test, selecting the lag order 7, does not contain the constant and time trend, calculated ADF statistics is -24.22338, and at the 1% level of ADF statistics for the critical value -2.565453, indicating that at least we can reject the null hypothesis of unit root in the existence of confidence level 99%, namely the stock daily return series is R stationary.
Similarly to the launch of stock index futures in front of the benefits of ADF unit root test sequence R1 rate, selecting the lag order 5, also includes constant and time trend, calculated ADF statistics is -19.11190, and at the 1% level of ADF statistics for the critical value -2.565984, indicating that at least we can reject the null hypothesis are unit root at the 99% confidence level, namely the stock daily return series is R1 stationary.
Similarly to the launch of stock index futures returns after the sequence R2 ADF unit root test, selecting the lag order 4, also includes constant and time trend, calculated ADF statistics is -21.90474, and at the 1% level ADF statistics of the critical value is -2.565907, indicating that at least we can reject the null hypothesis for units root at 99% confidence level, namely the stock daily return series is R1 stationary.
2.ARCH effect test
Self test method most commonly used autoregressive conditional heteroscedasticity test is the Lagrange multiplier method, namely LM test. Inspection of residual sequence R after fitting the presence of the ARCH effect, the use of Eviews6.0 software, do ARCH-LM test for 8 period lag residuals after fitting:
At a given significance level 1% and 8 degrees of freedom case, the LM value is equal to 500.7502, concomitant probability p 0, less than the 0.01 significance level, so the residual sequence exists significant ARCH effect, suitable for the use of GARCH model.
Similarly, residual test sequence R1 and sequence R2 after fitting the presence of the ARCH effect, LM value of the concomitant introduction respectively are 0.00000., less than 0.01, all ARCH effect exists in the residual sequence R1 and R2, suitable for the use of GARCH model.#p#分頁標題#e#
3.GARCH model
The general formula for the GARCH model:
(4-1)
(4-2)
(4-3)
Among them, (4-1) represents the mean equation yields sequence R; (4-3) represents the variance equation, which is composed of ARCH (P) and GARCH (q) components (i=1, ai,...... P J (j=1) and β,... ..Q) are the coefficients of ARCH and GARCH terms
In order to launch investigation of India stock index of India stock index, dummy variable, where Dt=0 (t=1989 year in April 12th to June 12, 2000), Dt=1 (t=2000 year in June 12th ~ April 12, 2010).

A, India NIFTY index and index futures
The full name of S&P CNX NIFTY50 NIFTY index, also called the standard & Poor's 50 stock market index, is the national stock exchange of India (NSE)'s main index, it is a market value weighted index. The index of 50 stocks selected from 22 industries, the average stock trading volume of the last six months the total stock exchange listing in the national stock exchange of India of 45124% April 10, 2007, its market capitalisation accounted for about 57192% of the total value of. So the NIFTY index is an ideal stock price index futures index.
National stock exchange of India (NSE) in 2000 June launch of the NIFTY index futures, and permit the Singapore Stock Exchange (SGX) in 2000 September launch of the NIFTY index futures, in order to increase the volume of NSE market and NIFTY stock index futures. At present, the NIFTY stock index futures has become a stock index futures contract before the turnover of ten world. According to the British "futures options weekly", 2006 1-6 month NIFTY futures contracts trading volume for the 38850982 Zhang Heyue, ranked fourth in the world. [this article from: lunwen.1kejian.com]
Two, empirical research
(a) the stock index daily return rate of descriptive statistics
The daily closing price of India stock index sequence selection, distribution system of India stock market rate of return. The data are from the national stock exchange of India (NSE) database, taking into account the national stock exchange of India launched the N IFTY stock index futures at home in June 12, 2000, from April 12, 1989 to April 12, 2010 a total of 4724 N IFTY index.
Daily return series of R index has the characteristics of left deviation, kurtosis and heavy tail. The skewness and kurtosis values from =-0.08684 =9.155324, and the standard normal distribution (S=0, K=3), on the yield of skewness value is negative, showed that the distribution of the Hang Seng Index daily return is left (negative) deviation, kurtosis value is positive and significantly higher than the normal distribution of 3, showed that the India stock index the return distribution density curve tails off to the left, characteristic is extremely obvious peak and fat tail distribution. While the JB normality test also shows that the p value close to 0, indicating at least can reject the null hypothesis at the 99% confidence level, namely the stock daily return series obviously different Yu Zheng normal distribution, so we can see that the NIFTY index daily return rate relief wavy, has obvious volatility clustering. Preliminary can determine its fluctuation has ARCH effect. [this article from: lunwen.1kejian.com]#p#分頁標題#e#
(two) the establishment of data processing and model
1 stationary test
Using Eviews 6 to yield sequence R ADF unit root test, selecting the lag order 7, does not contain the constant and time trend, calculated ADF statistics is -24.22338, and at the 1% level of ADF statistics for the critical value -2.565453, indicating that at least we can reject the null hypothesis of unit root in the existence of confidence level 99%, namely the stock daily return series is R stationary.
Similarly to the launch of stock index futures in front of the benefits of ADF unit root test sequence R1 rate, selecting the lag order 5, also includes constant and time trend, calculated ADF statistics is -19.11190, and at the 1% level of ADF statistics for the critical value -2.565984, indicating that at least we can reject the null hypothesis are unit root at the 99% confidence level, namely the stock daily return series is R1 stationary.
Similarly to the launch of stock index futures returns after the sequence R2 ADF unit root test, selecting the lag order 4, also includes constant and time trend, calculated ADF statistics is -21.90474, and at the 1% level ADF statistics of the critical value is -2.565907, indicating that at least we can reject the null hypothesis for units root at 99% confidence level, namely the stock daily return series is R1 stationary.
2.ARCH effect test
Self test method most commonly used autoregressive conditional heteroscedasticity test is the Lagrange multiplier method, namely LM test. Inspection of residual sequence R after fitting the presence of the ARCH effect, the use of Eviews6.0 software, do ARCH-LM test for 8 period lag residuals after fitting:
At a given significance level 1% and 8 degrees of freedom case, the LM value is equal to 500.7502, concomitant probability p 0, less than the 0.01 significance level, so the residual sequence exists significant ARCH effect, suitable for the use of GARCH model.
Similarly, residual test sequence R1 and sequence R2 after fitting the presence of the ARCH effect, LM value of the concomitant introduction respectively are 0.00000., less than 0.01, all ARCH effect exists in the residual sequence R1 and R2, suitable for the use of GARCH model.
3.GARCH model
The general formula for the GARCH model:
(4-1)
(4-2)
(4-3)
Among them, (4-1) represents the mean equation yields sequence R; (4-3) represents the variance equation, which is composed of ARCH (P) and GARCH (q) components (i=1, ai,...... P J (j=1) and β,... ..Q) are the coefficients of ARCH and GARCH terms
In order to launch investigation of India stock index of India stock index, dummy variable, where Dt=0 (t=1989 year in April 12th to June 12, 2000), Dt=1 (t=2000 year in June 12th ~ April 12, 2010).
Model into:
(4-4)
(4-5)
(4-6)
By using ARCH (1) GARCH (1), ARCH (1) GARCH (2), ARCH (2) GARCH (1) and ARCH (2) GARCH (2) model fitting of the conditional variance equation, the results are as follows:#p#分頁標題#e#
(4-7)
2 the exchange supervision
Stock index futures exchange hand using technology, advantage and the information itself, occur to constrain trading violations by establishing a series of rules and regulations. On the other hand, improve the exchange regulatory system, establishing an internal supervision (around eighty-eighth pages) (continued from page eighty-sixth) rules and procedures, effectively prevent the occurrence of insider trading.
(two) enhanced transparency [futures market index this information from: lunwen.1kejian.com]
Disclosure of information
Including the quality information and quantity of information disclosure, the former refers to the coherence of information organization's overall business objectives, risk strategy, transaction behavior and the goal as well as the internal control disclosure risk measures. The latter refers to the behavior of market, credit risk, market liquidity, profitability, market risk information disclosure. Enhance the transparency of market information to enable investors to the stock index futures, detailed, clear understanding of transaction and the changes of the market, the investors are no longer blindly follow the trend, false information from malicious publishing misleading help, enhance the stability of the market, so as to prevent the liquidity risk and market risk.
(three) the management mechanism to deal with unexpected risk
Emergency risk management mechanism can be carried out from the following aspects: A. prevent international hot money over the impact of stock index futures and spot market. To interfere with B. government, which mainly includes the policy guidance, to formulate laws, market transactions and capital to rescue the market, preventing market manipulation, prevention of unexpected market risk. The government can establish the risk management of the fund, so as to stabilize the market risk of sudden. C. in the actual operation, the reasonable introduction of fuse mechanism. In the face of unexpected events in front, the appropriate use of fuse mechanism can stop the panic selling, contribute to the rational market operation. [this article from: lunwen.1kejian.com]
(four) reduce policy intervention
When significant risk of economic crisis, the political crisis and the impact of capital can't resist, it is necessary for the government, also have the obligation to moderate intervention, but under normal circumstances, China should respect the laws of the market. Stock index futures for stock market investors to provide the system arrangement of risk, can avoid the risk of stock market, there is excessive speculation conducive to inhibit the stock market. Therefore, management should respect the laws of the market, reduce the stock market intervention, in order to facilitate the stock market and stock index futures trading in accordance with the law of value operation, reduce the impact of policy on the stock market and the stock index futures market.

Reference.#p#分頁標題#e#

Robinson G.The Effects of Futures Trading on Cash Markets Volatility：Evidence from London Stock Exchange[J].Review of FuturesMarkets，1994（2）：429-459.
　　[7]Hsinan Hsu，Janchung Wang.Price Expectation and the Pricing of Stock Index Futures[J].Review of Quantitative Finance and Accounting，2004（23）：167-184.